Machine Learning Engineer I - Clinical Data Science - Digital and Technology Partners - Hybrid/Onsite

Machine Learning Engineer I - Clinical Data Science - Digital and Technology Partners - Hybrid/Onsite, Req#3025164

This is hybrid/onsite position, at corporate location is 150 E 42nd Street

Machine Learning Engineer I will be primarily responsible for contributing to the development and enhancement of machine learning applications and systems. They will work closely with other engineers and data scientists to design and implement scalable and efficient machine learning systems.

Essential Duties and Responsibilities

1. Primary Developer Responsibility:
   • Play a central role in the machine learning system development while coordinating with a Senior or Lead engineer for overarching project management.
   • Contribute significantly to the integration of machine learning systems into broader organizational processes and workflows, ensuring alignment with overall project objectives overseen by higher-level engineers.
   • Work in collaboration with cross-functional teams, including data scientists and product managers, assisting in the successful deployment and maintenance of machine learning models.
   • Actively monitor deployed models and coordinate with the Senior Machine Learning Engineer to make necessary updates, ensuring the models’ continued performance and reliability.
2. Technical Leadership:
   • Provide technical leadership and mentorship to junior engineers and other team members.
   • Facilitate knowledge sharing and professional development within the team.
   • Act as a point of contact for technical queries related to machine learning system within the team.
3. Research and Development:
   • Stay abreast of the latest advancements and trends in the field of software engineering and machine learning.
   • Conduct research to identify new methods and techniques that can be applied to future projects.
   • Lead initiatives to test and implement new technologies and frameworks.
4. Additional Responsibilities:
   • Effectively communicates statistical and technical ideas and results to non-technical stakeholders in written and verbal form to ensure decision points and their impact are clearly understood by all audiences
   • Develop and maintain project work plans, including critical tasks, milestones, timelines, interdependencies, and contingencies.  Tracks and reports progress.  Keeps stakeholders apprised of project status and implications for completion. 
   • Prepare clear, well-organized project-specific documentation, including, at a minimum, analytic methods used, key decision points and caveats, with sufficient detail to support comprehension and replication. 
   • Mentor other analysts on how to a) determine appropriate statistical analysis methods, b) leverage appropriate programing languages and tools, and c) generate and interpret statistical analysis outputs.
   • Share development and process knowledge with other analysts in order to assure redundancy and continuously builds a core of analytical strength within the organization.
   • Adheres to corporate standards for performance metrics, data collection, data integrity, query design, and reporting format to ensure high quality, meaningful analytic output.
   • Works closely with IT on the ongoing improvement of Mount Sinai’s integrated data warehouse, driven by strategic and business needs, and designed to ensure data and reporting consistency throughout the organization.
   • Demonstrates advanced level proficiency with the principles and methodologies of process improvement. Applies these in the execution of responsibilities in support of a process focused approach.
   • Other duties as assigned.

Requirements

?    Bachelor?s degree in Computer Science, Data Science, or a related field.
?    Strongly Preferred: 4+ years of relevant experience in machine learning, back-end software development, or a related field.
?    Proficiency in machine learning frameworks, programming languages, and tools.
?    Proficient in programming languages such as Python, Java, and Scala
?    Strong experience with SQL.
?    Strong experience with Big Data technologies like Apache Spark.
?    Knowledge and experience with at least one cloud system among AWS, Azure, or Google Cloud.
?    A proven track record in developing and deploying efficient and reliable machine learning systems.
?    Strong leadership and communication skills.
 

, 271 - DTP Clinical Data Science - MSH, Mount Sinai Hospital